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Enregistrement W2605707138 · doi:10.1182/blood.v128.22.1705.1705

CD200 Is a Marker of LSC Activity in Acute Myeloid Leukemia

2016· article· en· W2605707138 sur OpenAlexaff
Jenny Ho, Stephanie M. Dobson, Jessica McLeod, Liqing Jin, Stanley W.K. Ng, Amanda Mitchell, Liran I. Shlush, Sasan Zandi, Kolja Eppert, Mark D. Minden, John E. Dick, Jean Wang

Notice bibliographique

RevueBlood · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensMcGill University Health CentreUniversity of TorontoPrincess Margaret Cancer CentreMcGill UniversityUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésCD34CD38Stem cellPopulationMyeloid leukemiaBiologyLeukemiaMyeloidHaematopoiesisImmunologyBone marrowStem cell markerMolecular biologySide populationCancer researchMedicineCancer stem cellCell biology

Résumé

récupéré en direct d'OpenAlex

Abstract Acute myeloid leukemia (AML) is a hierarchical disease in which the bulk blast population is sustained by a minority population of leukemia stem cells (LSC). Evidence of functional heterogeneity in the LSC compartment, including variable responses to chemotherapy, underscores the importance of examining the entire stem cell compartment in studies of LSC biology. However, there are currently no phenotypic markers that can consistently segregate LSCs within the leukemic blast population. Although LSC activity is most often enriched in the CD34+CD38- cell fraction, LSCs are also frequently detected in other phenotypic fractions, and in some cases are absent from CD34+ fractions. Thus, LSC studies that focus only on CD34+CD38- blasts may miss biologically important clones that are present in other phenotypic cell fractions. To identify novel markers that will enable better enrichment of LSC activity, we examined gene expression data obtained from functionally validated LSC+ and LSC- cell fractions sorted from primary AML samples, and identified CD200 as a candidate cell surface marker for LSCs. In normal adult bone marrow and cord blood samples, CD200 is expressed on >95% of CD34+CD38- cells, and expression decreases on CD34+38+ cells, suggesting that CD200, similar to CD34, is a stem cell marker. Flow cytometric analysis of AML patient samples (n=57) demonstrated that CD200 expression was present on a greater proportion of CD45dim blasts compared to CD45high non-blast populations (69.2% vs 4.5%, p<0.0001) and was significantly higher on CD34+ compared to CD34- cells (RFI 51.7 vs 3.5, p<0.0001). Although CD200 expression correlated with CD34 expression in many cases, some samples with low to no CD34 expression had high CD200 expression on CD45dim blasts, suggesting that CD200 can be used to identify CD34- LSCs. To test whether CD200 can segregate LSC activity within the CD45dim blast population, we sorted 14 primary AML samples into cell fractions based on CD45 and CD200 expression followed by transplantation into cohorts of NSG mice. AML samples were prescreened for leukemic engraftment ability and were selected for sorting if: 1) CD45dim blasts comprised both CD200+ and CD200- cells or 2) the CD200+ fraction was <5% of bulk cells. In 7 of 14 patients, LSC activity was enriched within the CD200+ fraction (CD200+ LSCs). For example, in AML40, in which CD200+ cells constituted only 5% of the bulk, as few as 5000 CD200+ blasts generated a leukemic graft at a mean level of 20.6%, whereas up to 500,000 CD200- blasts generated no graft. Importantly, LSC activity in these samples could not be segregated by CD34/CD38 expression; in contrast, the CD200+ fraction encompassed all cell fractions with LSC activity regardless of CD34/CD38 phenotype. In 1 of 14 patients, LSC activity was present in both the CD200+ and CD200- fractions. In the remaining 6 patients, LSC activity was enriched in the CD200- fraction (CD200- LSCs). In these samples, <3% of the bulk population expressed CD200; in 5 of the 6 samples, CD200+ cells generated multi-lineage (CD19+ B plus CD19‒CD33+ myeloid) rather than leukemic grafts, consistent with the presence of pre-leukemic-HSCs (preL-HSCs) in this cell fraction. In 2 additional AML patient samples that generated multi-lineage rather than leukemic grafts following transplantation of bulk cells, we refined our sorting strategy and were able to separate CD200+ LSCs from CD200+ preL-HSCs as evidenced by mutational analysis of xenografts. High CD200 expression was significantly associated with shorter overall survival in univariate analysis in multiple independent AML cohorts, but was not significant in multivariate analysis due to association with NPM1 mutation. NPM1-mutated samples exhibited low CD200 expression on the bulk cells. Interestingly, 7 of the 9 AML patients with CD200+ LSCs had normal karyotype and NPM1 mutation. Our results demonstrate that a CD200-based sorting strategy can successfully enrich and/or segregate LSC activity, and separate LSCs from preL-HSCs in primary AML patient samples. This will now enable direct functional studies of the biological properties of these related but distinct stem cell populations. Furthermore, CD200 will be a valuable tool for the study of LSCs in the subset of NPM1-mutated AML. Disclosures No relevant conflicts of interest to declare.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,005

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,016
Tête enseignante GPT0,283
Écart entre enseignants0,268 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2016
Routes d'admission1
Résumé présentoui

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